This pictorial examines how long-term, thing-centered documentation can function as a practice of noticing in everyday life, where meaning emerges not from individual events but through sustained attention to mundane arrangements, absences, and repetitions, as well as through processes of human–thing co-configuration. Drawing on a seven-year collection of daily breakfast photographs, the work captures presence and absence through simple table settings—plates, cups, and their shifting arrangements. Each image follows a strict rule: one side marks the author's breakfast, while the other records others, an empty setting, or complete absence. Through repetition, the images form a visual archive in which relationships and temporal rhythms emerge primarily through the images themselves. This pictorial invites designers and researchers to consider how mundane assemblages can be engaged as a method for noticing how memory, routine, and identity are shaped over time.

Increasing amounts of sensor-augmented research objects have been used in design research. We call these objects Data-Enabled Objects, which can be integrated into daily activities capturing data about people’s detailed whereabouts, behaviours, and routines. These objects provide data perspectives on everyday life for contextual design research. However, data-enabled objects are still computational devices with limited privacy awareness and nuanced data sharing. To better design data-enabled objects, we explore privacy design spaces by inviting 18 teams of undergraduate design students to re-design the same type of sensor-enabled home research camera. We developed the Connected Peekaboo Toolkit (CPT) to support the design teams in designing, building, and directly deploying their prototypes in real home studies. We conducted Thematic Analysis to analyze their outcomes which led us to interpret that privacy is not just an obstacle but can be a driver by unfolding an exploration of possible design spaces for data-enabled objects.

Designing future IoT ecosystems requires new approaches and perspectives to understand everyday practices. While researchers recognize the importance of understanding social aspects of everyday objects, limited studies have explored the possibilities of combining data-driven patterns with human interpretations to investigate emergent relationships among objects. This work presents Thing Constellation Visualizer (thingCV), a novel interactive tool for visualizing the social network of objects based on their co-occurrence as computed from a large collection of photos. ThingCV enables perspective-changing design explorations over the network of objects with scalable links. Two exploratory workshops were conducted to investigate how designers navigate and make sense of a network of objects through thingCV. The results of eight participants showed that designers were actively engaged in identifying interesting objects and their associated clusters of related objects. The designers projected social qualities onto the identified objects and their communities. Furthermore, the designers changed their perspectives to revisit familiar contexts and to generate new insights through the exploration process. This work contributes a novel approach to combining data-driven models with designerly interpretations of thing constellation towards More-Than Human-Centred Design of IoT ecosystems.

The home is a rich context for design research to study things and the Everyday. However, home is also a place of utmost privacy for most people. To better understand this context through an observational artifact without impacting privacy, we designed the Peekaboo cam that enables inhabitants to control their data release actively or passively. The Peekaboo cam is an observational research camera with a coverable lens. We validate in a field study in two homes for 14 days. The resulting photo streams provide qualitative insights on Everyday things in transition. We suggest four design guidelines for observational artifacts for home ecologies.